Fork of PyO3 adding batch serialization and validation for Django. Upstream: github.com/PyO3/pyo3
⚡ Auto-JIT your Python code with Numba @njit + optional AOT compilation 🚀 Numeric-heavy code, boosted fast 🏎️
PerfLens is a visual Python performance studio (PySide6) that turns cProfile/tracemalloc + stack sampling into interactive flame graphs, timeline traces, memory heatmaps, and call graphs—plus Diff Mode, an optimization coach, session save/load, and one-click HTML reports. Single-file app.py with a zero-input demo.
Modular Spectrum of Pi: reference implementation of the Stride-6 engine. Unifies Chudnovsky's series with DSP polyphase decomposition in Z/6Z. Validated at 100M digits with 95% parallel efficiency. Features a Shared-Nothing architecture to bypass the memory wall and maximize cache alignment.
Python Performance Tester & More...
The Python Performance Benchmark Tool is a comprehensive command-line utility designed to benchmark the performance of various unoptimized computations in pure Python. It enables developers and users to analyze the computational performance of different Python versions, allowing for informed decisions when selecting the optimal interpreter.
Boost Python's performance using Cython – a bridge between Python's simplicity and C's efficiency. Explore and learn how Cython accelerates code execution.
A performance optimization library based on mypyc, similar to numba but supporting accelerating general Python code.
Pure CPU Conway's Game of Life - 2,500x speedup, 100M cells in 274ms. No GPU.
Pushing Python deployments to silicon limits: an empirical study of cache locality, TLB misses, pointer chasing, and constructive L3 cache sharing for high-throughput ML pipelines.
Repository for Python performance case studies focusing on I/O bottlenecks and CPU complexity.
a demo shows how to use c to acclerate the execute effciency of python
A hands-on guide to Advanced Python Engineering covering CPython internals, memory management, data structures, algorithms, namespaces, OOP, concurrency, optimization, and security. Features practical experiments, benchmarks, engineering notes, and production-grade capstone projects for building scalable, high-performance applications.
A simple API for unit testing a Python project's performances and memory leaks ⚡
Benchmarks de rendimiento con multithreading: Python 3.12 vs 3.14 con y sin GIL
Make your Python code faster with one decorator: compiles numeric Python (math, helpers, NumPy arrays) to Rust, and falls back to normal Python so results never change.
Python import-time profiler that finds which imports you can safely make lazy.
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